Establishment and Evaluation of an Ensemble Bias Correction Framework for the Short-Term Numerical Forecasting on Lower Atmospheric Ducts

Based on the COAWST (Coupled Ocean–Atmosphere–Wave–Sediment Transport) model, this study developed an atmospheric refractivity forecasting model incorporating ensemble bias correction by combining five bias correction algorithms with the Bayesian Model Averaging (BMA) method. Hindcast tests conducte...

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主要な著者:	Huan Guo, Bo Wang, Jing Zou, Xiaofeng Zhao, Bin Wang, Zhijin Qiu, Hang Wang, Lu Liu, Xiaolei Liu, Hanyue Wang
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2025-12-01
シリーズ:	Journal of Marine Science and Engineering
主題:	atmospheric duct Bayesian model averaging deep learning ensemble forecasting model bias correction model evaluation
オンライン･アクセス:	https://www.mdpi.com/2077-1312/13/12/2397
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